Package: SimBiology.fit
Results object containing estimation results from leastsquares regression
The LeastSquaresResults
object is a superclass of two results
objects: NLINResults object
and OptimResults object
. These objects contain estimation results from
fitting a SimBiology^{®} model to data using sbiofit
with any supported algorithm.
If sbiofit
uses the nlinfit
estimation
algorithm, the results object is the NLINResults
object. If
sbiofit
uses any other supporting algorithm, then the results
object is an OptimResults
object. See the sbiofit
function for the list of supported algorithms.
boxplot  Create box plot showing the variation of estimated SimBiology model parameters 
fitted  Return simulation results of SimBiology model fitted using leastsquares regression 
plot  Compare simulation results to the training data, creating a timecourse subplot for each group 
plotActualVersusPredicted  Compare predictions to actual data, creating a subplot for each response 
plotResidualDistribution  Plot the distribution of the residuals 
plotResiduals  Plot residuals for each response, using time, group, or prediction as xaxis 
predict  Simulate and evaluate fitted SimBiology model 
random  Simulate SimBiology model, adding variations by sampling error model 
summary  Return structure array that contains estimated values and fit quality statistics 
GroupName  Categorical variable representing the name of the group associated
with the results, or [] if the
'Pooled' namevalue pair argument was set to
true when you ran
sbiofit . 
Beta  Table of estimated parameters where the jth row
represents the jth estimated parameter
β_{j}. It contains
transformed values of parameter estimates if any parameter transform is
specified. Standard errors of these parameter estimates
( It can also contain the following variables:

ParameterEstimates  Table of estimated parameters where the jth row
represents the jth estimated parameter
β_{j}. This table
contains untransformed values of parameter estimates. Standard
errors of these parameter estimates
( It can also contain the following variables:

J  Jacobian matrix of the model, with respect to an estimated parameter,
that is,
$$J(i,j,k)={\frac{\partial {y}_{k}}{\partial {\beta}_{j}}}_{{t}_{i}}$$
where t_{i} is the ith time point, β_{j} is the jth estimated parameter in the transformed space, and y_{k} is the kth response in the group of data. 
COVB  Estimated covariance matrix for Beta , which is
calculated as: COVB = inv(J'*J)*MSE . 
CovarianceMatrix  Estimated covariance matrix for
ParameterEstimates , which is calculated as:
CovarianceMatrix = T'*COVB*T , where T =
diag(JInvT(Beta)) .
For instance, suppose you
specified the logtransform for an estimated parameter

R  Residuals matrix where R_{ij} is the residual for the ith time point and the jth response in the group of data. 
LogLikelihood  Maximized loglikelihood for the fitted model. 
AIC  Akaike Information Criterion (AIC), calculated as AIC =
2*(LogLikelihood + P) , where P is the
number of parameters. 
BIC  Bayes Information Criterion (BIC), calculated as BIC =
2*LogLikelihood + P*log(N) , where N is
the number of observations, and P is the number of
parameters. 
DFE  Degrees of freedom for error, calculated as DFE =
NP , where N is the number of
observations and P is the number of
parameters. 
MSE  Mean squared error. 
SSE  Sum of squared (weighted) errors or residuals. 
Weights  Matrix of weights with one column per response and one row per observation. 
EstimatedParameterNames  Cell array of character vectors specifying estimated parameter names. 
ErrorModelInfo  Table describing the error models and estimated error model
parameters.
There are four builtin error models. Each model defines the error using a standard meanzero and unitvariance (Gaussian) variable e, the function value f, and one or two parameters a and b. In SimBiology, the function f represents simulation results from a SimBiology model.

EstimationFunction  Name of the estimation function. 
DependentFiles  File names to include for deployment. 
Note
Loglikelihood
, AIC
, and
BIC
properties are empty for
LeastSquaresResults
objects that were obtained before
R2016a.
NLINResults object
 OptimResults object
 sbiofit
 sbiofitmixed